Competition between investment firms is more intense than ever before as firms are expected to be able to beat the S&P 500 on a regular basis to retain and attract new investors. The market is evolving beyond previously established theories however investors still expect strong and consistent returns. Traditional tools and fundamental analysis are no longer enough to stay competitive in the contemporary market. Investment firms need to stay one step ahead in order to be the first to recognize trends and take advantage of opportunities. To stay competitive they are looking to employ the most advanced tools to enhance performance. Algorithmic trading is now a growing trend filling this void. Algorithmic “Buy” and “Sell” orders account for 60%-70% of the US equity market volume. Previously, only large investment firms and hedge funds were able to utilize these advanced mathematical models but I Know First: Daily Market Forecast, a financial start-up, has developed an advanced self-learning algorithm that is being employed by professionals and retail investors alike.
This article was written by the I Know First Research Team.
One of the most common themes you find in many mythologies across the globe is that of order and chaos. The world as we know it, in all its orderly (or at least more orderly than not) glory, is emerging from the state of complete and utter entropy. This can be seen as a metaphor for many things, from organic life coming into existence in the primordial broth to the way the first humans explored their environment, rationalizing their experiences in ways that made sense in the existing system of knowledge. Rationalizing is the keyword here: it does not take a stretch of the imagination to view
This article was written by the I Know First Research Team.
The traditional finance sector as we know it is going through a process of change. As new technologies disrupt the conventions and dogmas, whole industries are transformed, keeping pace with the rapidly-changing world. Finance is no exception to this rule, and, as a sphere that lives and breathes quantitative data (lots and lots of quantitative data!), it has been particularly sensitive to the rise of the artificial intelligence, a technology driven by the computers’ newfound ability to crunch massive troves of data. And while it may or may not be too early to speak of the financial industry
This article was written by the I Know First Research Team.
Currently, the world is abuzz with the talk of millennials – the tech-savvy generation of digital natives who were born in the period from 1984 to 1996. Or from 1980 to 2000, if you ask the Time Magazine, which smartly adds “depending on whom you ask” to this definition. Or from 1977 to 1994, if we cite Newsweek. This disparity in itself suggests a certain confusion around the whole affair with millennials. Even the timeframes we just mentioned
This article was written by the I Know First Research Team.
In late 18th century, the British textile industry spearheaded a process that would become known as the First Industrial Revolution, which saw first factories appear and new manufacturing processes introduced. Then, the Second Industrial Revolution followed on the back of railroads and telegraphs enabling quick movement of people and ideas and Henry Ford’s moving assembly line beefing up the industrial output to new heights. The Third Industrial Revolution saw manufacturing go digital, with computers brought in to run and streamline the process, and now, some are speaking of a Fourth
This article was written by the I Know First Research Team.
“Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence.”
Virginia Marie Rometty, head of IBM.
Robots In The Workplace
As the world embraces the power of artificial intelligence and machine learning, whole industries are transformed to reflect this new reality. AIs are now helping taxi companies identify spots that would see lots of ride requests coming in. They could
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